Advanced Predictive Modelling
This module builds on the concepts introduced in the module Fundamentals of Predictive Modelling.
In this module, learners are introduced to model development for categorical dependent variables. Binary dependent variables are encountered in many domains such as risk management, marketing and clinical research and this unit covers detailed model building processes for binary dependent variables. Additionally, a primary goal of the module is for students to be able to select and successfully apply appropriate advanced regression models in applied settings.
The module will culminate with multinomial models and ordinal scaled variables.
Core Reading List:
Mastering Predictive Analytics with R - Second Edition James D. Miller, Rui Miguel Forte Publisher Packt Publication date: August 2017
Predictive Analytics with Python, 1st Edition Alvaro Fuentes Publisher Packt
- Accreditation: ECTS Accredited (EQF7)
- Total workload: 150 hours
- Requires extra purchases (outside texts, etc.): Yes, purchases required
- ID verification: Required
- Admission requirements: Application required
- Minimum education requirement for students: Undergraduate
Candidates who apply for this course must have a recognised undergraduate degree or equivalent. Candidates without a degree but with other relevant qualifications and/or work experience can also be considered.
English language competency at an IELTS 6.5 (or equivalent) is required of all applicants whose first language is not English. Where students can demonstrate previous substantial studies or work experience in English, this requirement can be waived.